Evolving and improving protein stability for enhanced biopharmaceuticals

The importance of antibody-based therapeutics is now well established and this expanding sector, in which the UK is a large stakeholder, now has yearly sales of greater than $75 billion. However, the production and formulation of biopharmaceuticals can be problematic, jeopardising their successful development. Specifically, protein self-association results in major hurdles which must be overcome for the translation of a promising candidate to a blockbuster bio-therapeutic and can result in the failure of promising candidate biologics during pre-clinical development. The ability to predict and/or detect sequences prone to aggregation, thus, is the holy grail of the biologics industry.
In this studentship we will develop new understandings of how and why proteins aggregate and which are likely to be unsuitable for bioprocessing and development. We will achieve this using protein engineering to evolve new protein sequences with reduced/enhanced stability and/or aggregation propensity using a split-beta-lactamase system we have recently developed (Foit et al., Molecular Cell, 2009 and Saunders, Brockwell, Radford et al., Nature Chemical Biology, 2016). We will then use sophisticated biophysical methods (e.g. SEC-MALLS, DLS, HX, NMR and FCS) to measure the stability, dynamics and aggregation propensity of the resulting sequences. Finally, we will determine how the bioprocess environment (flow and interaction at interfaces) affects the behaviour of the selected protein sequences (using custom build flow devices developed as part of an on-going collaboration with Professor Nik Kapur (Mechanical Engineering)). We will focus on proteins with an immunoglobulin (Ig) fold, including I27, beta2m (non-aggregating and aggregating model systems) as well as scFvs with known differences in bioprocess behaviour (provided by MedImmune). The model proteins will be studied both as single domains (100 aa), and as polyproteins (mimicking antibody light and heavy chains). These are scaffolds of primary importance in biopharma, including our industrial collaborator. The goal is to discover the mechanisms and determinants of protein self-assembly and why some sequences aggregate with/without flow, whilst others do not.